Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods

Machine tools are one of the important parts of manufacturing process that could help company to achieving high competitiveness in the marketplace. In addition, the quality of their outputs depends on their machines and therefore every company should select the best machine by itself. Also, a choice of appropriate machine tool is very significant for a manufacturing company as it helps to reach high productivity and efficiency. Furthermore, market offers variety kind of machines with different brands. Besides, there are many criteria with respect to numerous alternatives that should be considered as part of proper machine tool selection, such as cost, operative flexibility, safety, etc. Consequently selection of machine tool can be regarded as a multiple-attribute decision making (MADM) problem. Generally, MADM methods deal with the process of selection of an alternative among number of different alternatives in the presence of usually conflict objectives and criteria. In this study two MADM methods, step-wise weight assessment ratio analysis (SWARA) and complex proportional assessment of alternatives with grey relations (COPRAS-G), were applied for machine tool evaluation and selection. This model is a hybrid model which integrates two MADM methods for improving the quality and accuracy of the selection. Literature survey was used to identify the most attractive criteria which influence the selection of a machine tool. Eight criteria for evaluation process include cost, operative flexibility, maintainability and service ability, size and physical, compatibility, safety, precision and productivity. More precisely, the first part of the proposed methodology, i.e. SWARA is useful for determining the importance of each criterion and calculating weight of each criterion, while the second part with COPRAS-G is useful for evaluating alternatives more precisely than usual crisp COPRAS and for ranking machine tool alternatives from the best to the worst ones. In evaluation process decision maker has to assess criteria which are not accurate. Grey relation analysis allows incorporating the vague and imprecise information in to the decision model. For illustration of the proposed methodology, a case study was explained in a manufacturing company in Karaj, Iran. This model can help managers to evaluate and select the best machine tool alternative based on own company strategies, resources, policies, etc. for their organization. DOI: http://dx.doi.org/10.5755/j01.ee.24.1.2822